English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Online platforms collect rich information about participants and then sharesome of this information back with them to improve market outcomes. In thispaper we study the following information disclosure problem in two-sidedmarkets: If a platform wants to maximize revenue, which sellers should theplatform allow to participate, and how much of its available information aboutparticipating sellers' quality should the platform share with buyers? We studythis information disclosure problem in the context of two distinct two-sidedmarket models: one in which the platform chooses prices and the sellers choosequantities (similar to ride-sharing), and one in which the sellers chooseprices (similar to e-commerce). Our main results provide conditions under whichsimple information structures commonly observed in practice, such as banningcertain sellers from the platform while not distinguishing betweenparticipating sellers, maximize the platform's revenue. The platform'sinformation disclosure problem naturally transforms into a constrained pricediscrimination problem where the constraints are determined by the equilibriumoutcomes of the specific two-sided market model being studied. We analyze thisconstrained price discrimination problem to obtain our structural results.

Quality Selection in Two-Sided Markets: A Constrained Price Discrimination Approach